oumi
Easily fine-tune, evaluate and deploy Qwen, Gemma, or any open weight LLM!
The Oumi MCP server enables Claude Desktop and Cursor users to access Oumi's AI model fine-tuning, evaluation, and deployment capabilities directly from their development environment. This integration allows developers to train, fine-tune, and deploy open-weight language models like Qwen, Gemma, and Llama without leaving their editor. It bridges Oumi's comprehensive model lifecycle platform—covering data preparation, training with techniques like LoRA and GRPO, evaluation across benchmarks, and deployment to inference endpoints—with MCP-compatible AI assistants for streamlined workflow automation.
Key Features
Use Cases
- 01Fine-tune a Qwen or Llama model on custom data for domain-specific tasks directly from Claude Desktop
- 02Evaluate multiple model variants on standard benchmarks to compare performance before deployment
- 03Deploy a fine-tuned model to a dedicated inference endpoint and test it interactively
- 04Synthesize and curate training datasets using LLM judges within your development workflow
- 05Distill large models like DeepSeek R1 671B into smaller, efficient variants for production use
- 06Launch remote training jobs on cloud GPU clusters and monitor progress from your editor
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oumi — FAQ
What is the Oumi MCP server?+
The Oumi MCP server is an integration that connects Oumi's end-to-end AI model training and deployment platform to Claude Desktop and Cursor, allowing you to fine-tune, evaluate, and deploy language models directly from your development environment.
How do I install the Oumi MCP server?+
Install Oumi via pip or uv with 'uv pip install oumi', then add the MCP server configuration to your Claude Desktop or Cursor settings file. The server runs locally and communicates with the Oumi CLI tools.
Which AI clients support the Oumi MCP server?+
The Oumi MCP server works with Claude Desktop and Cursor, as mentioned in the v0.8 release notes for Claude/Cursor integration.
Do I need API keys to use the Oumi MCP server?+
API keys are only required if you use commercial model providers (OpenAI, Anthropic, Fireworks, Together) or cloud platforms for remote training. Local training and inference with open models requires GPU access but no API keys.
Is the Oumi MCP server free to use?+
Yes, Oumi is fully open-source under the Apache 2.0 license. However, you may incur costs for cloud GPU compute, inference endpoints, or commercial API usage depending on your workflow.
What are the prerequisites for using Oumi?+
You need Python 3.8+ (Python 3.13 supported as of v0.6.0) and optionally GPU access for training. Install dependencies via pip/uv, and configure cloud credentials if running remote jobs.
How do I install oumi?+
Open the source repository on GitHub and follow its README. oumi is a mcp server — MCP Agents Market links you directly to the official repo.
Is oumi free?+
oumi is an open-source project hosted on GitHub. Check the repository for its license and any usage requirements.